HPLC-based online high-precision metering method for charging facilities and device thereof

Abstract

The application discloses a kind of based on HPLC's charging facility online high-precision metering method and device thereof.The method comprises: sending acquisition command to HPLC module through power line, and collecting voltage, temperature, pulse, clock signal, driving magnetic flux gate sensor real-time current signal acquisition, all signals are returned to platform by HPLC module;Firstly, real-time data is obtained by pretreatment, then real-time data is compared with standard source data, and the error of electric energy metering, clock synchronization error and harmonic influence error are calculated, and finally, the comprehensive error is calculated according to the three errors;Whether the comprehensive error exceeds threshold value, yes, it is judged that the measurement is unqualified, otherwise, it is judged that the measurement is qualified.The application systematically solves the real-time, economy, accuracy problem of charging facility verification, breaks through the limitation of traditional periodical verification, realizes the continuous metering performance tracking of 1 time per minute, discovers gradual failure such as CT saturation, ADC drift in time, and effectively improves the anti-interference ability and detection stability.

Description

Technical Field

[0001] This invention relates to an online high-precision metering method for charging facilities based on HPLC in the field of power systems, and more particularly to an online high-precision metering device for charging facilities based on HPLC. Background Technology

[0002] Currently, China has mandatory verification requirements for charging facilities with trade settlement functions. However, mainstream verification technologies, such as portable testing equipment and on-site testing vehicles that rely on manual operation, have significant limitations. Portable testing equipment cannot comprehensively cover all monitoring items required by mandatory verification (including appearance and functional inspection, operational error verification, clock timing error verification, interoperability testing, protocol consistency testing, and temperature acquisition, etc.). On-site testing vehicles are limited by the dispersed nature of charging facility sites and the limited verification resources (personnel and vehicles), resulting in low verification efficiency. Furthermore, they can only acquire discrete data of the facility at a specific moment, failing to achieve real-time monitoring around the clock and making it difficult to reflect the true continuous operating status of the facility.

[0003] Furthermore, existing verification technologies generally employ Hall effect sensors for energy metering. Charging facilities are typically deployed in complex outdoor environments, facing significant temperature variations (such as extreme weather), and the measurement accuracy of Hall effect sensors is easily affected by temperature, making it difficult to guarantee the long-term accuracy and reliability of energy metering. Simultaneously, discrete on-site verification methods cannot monitor the real-time operating conditions of charging piles, posing a risk of operators unauthorized replacement of the charging pile's metering unit, making supervision difficult. Therefore, there is an urgent need for a technology that can overcome these shortcomings and possess high-precision online verification capabilities to effectively support the national mandatory verification requirements for charging facilities and improve verification efficiency and regulatory capacity. Summary of the Invention

[0004] To address the technical problems of low verification efficiency and poor accuracy in existing charging facility measurement methods, this invention provides an online high-precision measurement method and apparatus for charging facilities based on HPLC.

[0005] This invention employs the following technical solution: an online high-precision metering method for charging facilities based on HPLC, wherein the charging facility is equipped with an HPLC module and a fluxgate sensor; the metering method includes the following steps: The system sends acquisition commands to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, and drives the fluxgate sensor to acquire current signals in real time. All signals are transmitted back to the platform through the HPLC module. First, the platform preprocesses the received signal to obtain real-time data. Then, the real-time data is compared with standard source data to calculate three errors: power metering error, clock synchronization error, and harmonic influence error. Finally, the comprehensive error is calculated based on the three errors. If the overall error exceeds the threshold, the measurement is deemed unqualified and a report is generated; otherwise, the measurement is deemed qualified and a corresponding certificate is generated.

[0006] This invention significantly improves efficiency through online verification of charging facilities based on HPLC. Traditional manual verification of a single charging pile takes 2 hours (including on-site disassembly, assembly, and testing), while this metrology method can reduce the time to within a few minutes through remote online verification. It can also support the concurrent verification of multiple charging piles. Through the deep integration of HPLC communication and metrology technology, it systematically solves the problems of real-time performance, economy, and accuracy in charging facility verification. It breaks through the limitations of traditional periodic verification, achieving continuous metrological performance tracking once per minute, and timely detection of gradual faults such as CT saturation and ADC drift. It solves the technical problems of low verification efficiency and poor accuracy in existing charging facility metrology methods.

[0007] As a further improvement to the above scheme, the formula for calculating the electricity metering error is as follows: e e = (( E meas - E std ) / E std )×100% In the formula, e e This indicates the electrical energy metering error. E meas This indicates the electrical energy value measured by the tested charging facility. E std This indicates the electrical energy value measured by a standard electricity meter.

[0008] Furthermore, the formula for calculating the clock synchronization error is as follows: e t = (( T local - T standard ) / T standard )×100% In the formula, e t This indicates the clock synchronization error. T local Indicates the local clock time of the tested charging facility. Tstandard Indicates the time of the standard time source.

[0009] Furthermore, the formula for calculating the comprehensive error is as follows: In the formula, e This represents the overall error. e h This indicates the harmonic influence error. α , β , c This represents the weighting coefficient.

[0010] Furthermore, E meas The calculation formula is: E meas = ( N meas ×3600) / (1000× t ) In the formula, N meas This indicates the pulse count of the meter under test. t Indicates the measurement time; E std The calculation formula is: E std = ( N std ×3600) / (1000× t ) In the formula, N std This indicates the standard meter pulse count.

[0011] As a further improvement to the above scheme, the HPLC module uses a π-type filter network for high-frequency noise isolation, and the filter network parameters are: inductance L=2mH, capacitance C=0.1μF; the fluxgate sensor uses a nanocrystalline alloy core, and the linear measurement range covers ±250A, and is equipped with an H-bridge drive circuit with 10kHz square wave excitation.

[0012] As a further improvement to the above scheme, the data acquisition command is issued using a TDMA time division multiple access mechanism with a time slot width of 10ms. The data packet structure includes a frame header of 0xAA55, a data length field, a command word field, payload data, a CRC16 check field, and a frame tail of 0x55AA. All signal return data carries a timestamp synchronized by the IEEE 1588 protocol, and the time synchronization deviation between the platform and the charging facility is less than 1μs.

[0013] As a further improvement to the above scheme, the output signal of the fluxgate sensor is sequentially passed through a bandpass filter and a two-stage amplification circuit, and then converted into a digital signal by a 24-bit Σ-Δ ADC; the fluxgate sensor has a built-in PT1000 temperature sensor, and the temperature signal is acquired through the PT1000 temperature sensor.

[0014] As a further improvement to the above solution, the platform performs temperature drift compensation on the current waveform data using a lookup table method, with the compensation range covering -40℃ to 85℃; when calculating the power metering error, the platform simultaneously analyzes the harmonic distortion rate in the current waveform, and triggers an early warning when the harmonic distortion rate exceeds a threshold.

[0015] This invention also provides an online high-precision metering device for charging facilities based on HPLC, which applies any of the above-described online high-precision metering methods for charging facilities based on HPLC; the device includes: The data acquisition system is used to send acquisition commands to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, drive the fluxgate sensor to acquire current signals in real time, and transmit all signals back to the platform through the HPLC module. The error detection system is used to first enable the platform to preprocess the received signal to obtain real-time data, then compare the real-time data with standard source data, calculate three errors: power metering error, clock synchronization error, and harmonic influence error, and finally calculate the comprehensive error based on the three errors. The over-limit determination system is used to determine whether the comprehensive error exceeds the threshold. If it does, the measurement is deemed unqualified and a report is generated; otherwise, the measurement is deemed qualified and a corresponding certificate is generated.

[0016] Compared with existing charging facility metering methods, the HPLC-based online high-precision metering method and apparatus for charging facilities of the present invention have the following advantages: 1. This HPLC-based online high-precision metrology method for charging facilities significantly improves efficiency through online verification of charging facilities. Traditional manual verification of a single charging pile takes 2 hours (including on-site disassembly, assembly, and testing), while this metrology method can reduce the time to within a few minutes through remote online verification. It can also support the concurrent verification of multiple charging piles. Through the deep integration of HPLC communication and metrology technology, it systematically solves the problems of real-time performance, economy, and accuracy in charging facility verification. It breaks through the limitations of traditional periodic verification, achieving continuous metrological performance tracking once per minute, and timely detection of gradual faults such as CT saturation and ADC drift. It solves the technical problems of low verification efficiency and poor accuracy in existing charging facility metrology methods.

[0017] 2. This HPLC-based online high-precision metering method for charging facilities enables integrated power line-communication transmission. This method reuses the charging pile's power supply line for data communication, eliminating the need for additional wiring and reducing deployment costs. It also supports high-frequency data transmission (10kS / s sampling rate), meeting the requirements of JJG 1148-2022 for dynamic energy metering. Furthermore, employing multi-band adaptive modulation technology (such as a 2-12MHz adjustable carrier), it maintains communication stability (bit error rate <10%) even under high-frequency switching noise (above 30kHz) from the charger. -6 ).

[0018] 3. This HPLC-based online high-precision metering method for charging facilities can achieve low-latency time synchronization. Based on an improved IEEE 1588 (PTP) protocol, this method achieves sub-microsecond synchronization (deviation <1μs) between the verification end and the standard clock source via the HPLC channel, ensuring the timing consistency of the metering data. Furthermore, it dynamically compensates for power line transmission delay, resolving the clock drift problem caused by network jitter in traditional RS-485 / 4G solutions.

[0019] 4. This HPLC-based online high-precision metrology method for charging facilities ensures secure encryption and data integrity. The method employs an encryption algorithm to perform end-to-end encryption of verification commands and metrological data, preventing man-in-the-middle attacks. Furthermore, each data packet is appended with a CRC-32 checksum, and abnormal data automatically triggers a retransmission mechanism (retransmission success rate >99.9%).

[0020] 5. The HPLC-based online high-precision metering method for charging facilities innovatively applies a fluxgate sensor to the current measurement of charging piles, which can achieve: (1) wide dynamic range and high-precision detection. Using closed-loop fluxgate technology, a current measurement accuracy of ±0.05% is achieved in the range of 5A-250A (better than the ±0.2% of the traditional Hall sensor), which is especially suitable for high-current fast charging scenarios (such as 800V high-voltage platforms). Furthermore, the measurement drift problem of charging piles in outdoor environments can be solved by using a temperature compensation algorithm (temperature drift <10ppm / ℃ from -40℃ to 85℃). (2) Harmonic anti-interference capability. The fluxgate sensor is based on the principle of magnetic field induction and has natural anti-interference capability against high-frequency harmonics (such as noise above 50kHz generated by the charger). Compared with traditional shunts, it can reduce the harmonic influence by more than 90%. Combined with real-time FFT analysis, harmonic components are dynamically eliminated to ensure that the fundamental energy metering error is ≤0.1%. (3) Non-contact measurement. Non-invasive installation (no need to disconnect the main circuit), supports online replacement and calibration, avoiding the risk of metering failure caused by magnetic saturation of traditional CTs (current transformers).

[0021] 6. The beneficial effects of this HPLC-based online high-precision metering device for charging facilities are the same as those of the metering methods described above, and will not be elaborated further here. Attached Figure Description

[0022] Figure 1 This is a flowchart of the online high-precision metering method for charging facilities based on HPLC according to Embodiment 1 of the present invention.

[0023] Figure 2 for Figure 1 The circuit diagram of the π-type filter network in the HPLC module of the metrology method. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0025] Example 1 Please see Figure 1 and Figure 2 This embodiment provides an online high-precision metrology method for charging facilities based on HPLC. This metrology method collects charging process data of the charging facilities on-site through a high-precision fluxgate sensor and uses a low-voltage power line high-speed carrier channel to transmit analog or digital signals at high speed, thereby realizing the online verification of electric vehicle charging facilities of State Grid Corporation of China and significantly improving the efficiency of mandatory verification of charging facilities.

[0026] In this embodiment, an HPLC module and a fluxgate sensor are installed in the charging facility. In addition, an online calibration module can be added to the charging facility to collect and analyze voltage, current, temperature and clock data in real time. The fluxgate high-precision sensor collects power data with an accuracy of ±0.2%.

[0027] The HPLC module employs a π-type filter network for high-frequency noise isolation, ensuring signal purity. The filter network parameters are: inductance L = 2mH and capacitance C = 0.1μF. The HPLC module uses HPLC to issue verification commands and transmit measurement data, supporting remote calibration of all parameters required by the charging pile verification procedure (JJG 1148-2022). As an option, this embodiment uses the QPD-600 chipset (supporting the CENELEC-A band, 9-95kHz) to achieve power line carrier communication. Furthermore, an impedance matching circuit (50Ω→1kΩ adaptation) is added to optimize long-distance power line transmission efficiency. This embodiment, through HPLC communication, can integrate data into the existing power grid system, solving the technical problem of data continuity for charging orders.

[0028] The fluxgate sensor employs a nanocrystalline alloy core with an initial permeability >50,000 and a linear measurement range covering ±250A. It is equipped with a 10kHz square wave excited H-bridge drive circuit, with the square wave excitation signal amplitude ±5V, driving the core to saturation via the H-bridge. In some embodiments, the fluxgate sensor can utilize dual closed-loop feedback control (current feedback loop + flux feedback loop), using a PID controller to adjust the H-bridge drive power in real time, compressing the core saturation time to within 5μs and ensuring a dynamic tracking accuracy of ±0.1% even at a current change rate of 100A / μs. For DC fast charging scenarios, a DC bias compensation coil (compensation current adjustable from 0-10mA) is added to eliminate zero-point drift caused by residual magnetism.

[0029] The measurement method includes the following steps.

[0030] 1. A data acquisition command is sent to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, driving the fluxgate sensor to acquire current signals in real time. All signals are transmitted back to the platform via the HPLC module. Voltage signals can be detected using a voltage sensor, and temperature signals can be detected using a temperature sensor.

[0031] In this embodiment, the physical layer of the communication protocol stack uses OFDM modulation with 128 subcarriers and a bandwidth of 2MHz, supporting QPSK / 16QAM adaptive switching. A spectrum sensing module (scanning the 2-30MHz band) can also be added to the physical layer to dynamically avoid frequencies with concentrated charging switch noise (such as 28kHz / 56kHz). Data acquisition commands are issued using TDMA (Time Division Multiple Access) with a time slot width of 10ms. The data packet structure includes a frame header (0xAA55), a data length field, a command field, payload data, a CRC16 check field, and a frame tail (0x55AA). An ARQ (Automatic Repeat Request) mechanism can be added to ensure a packet loss rate of <0.1%. All signal return data carries a timestamp synchronized according to the IEEE 1588 protocol, ensuring a time synchronization deviation between the platform and the charging facility of less than 1μs. This embodiment uses multi-carrier OFDM modulation and a deep learning channel equalization algorithm to guarantee a bit error rate of <10⁻ under 30kHz switching noise from the charging facility. 6 .

[0032] In this embodiment, the output signal of the fluxgate sensor passes through a bandpass filter and a two-stage amplification circuit, and is converted into a digital signal by a 24-bit Σ-Δ ADC (such as TI ADS131M08) to achieve a resolution of 0.1mA. In some embodiments, an 8192-point FFT can be performed on the current waveform to extract the 2nd to 50th harmonic components, and the power is weighted and corrected according to the harmonic weighting coefficients in Appendix B of JJG 1148-2022. The fluxgate sensor has a built-in PT1000 temperature sensor, and the core temperature drift is corrected by a lookup table method. This embodiment improves the anti-interference capability by modifying the original Hall sensor with a fluxgate sensor, and the online calibration accuracy and stability of the charging facility are high. In this embodiment, each calibration result generates a hash value and uploads it to the blockchain to ensure that it cannot be tampered with (compliant with NISTSP 800-82 standard). Moreover, a three-dimensional compensation table (temperature × current × frequency) for the fluxgate sensor can be established, and the compensation value can be output in real time by Lagrange interpolation to control the full-range temperature drift within ±5ppm / ℃.

[0033] Data packet example: { "timestamp": "2025-05-22T14:30:00.000Z", / / PTP synchronization time "voltage": [220.1, 219.8, ...], / / 1000 points / second "current": [32.45, 32.50, ...], "harmonic_THD": 2.1% / / Harmonic distortion rate } Second, the platform first preprocesses the received signal to obtain real-time data. Then, the real-time data is compared with standard source data to calculate three errors: power metering error, clock synchronization error, and harmonic interference error. Finally, a comprehensive error is calculated based on these three errors. The preprocessing process mainly involves raw data acquisition and synchronization, signal quality enhancement, temperature compensation processing, and data integrity verification.

[0034] 1. Raw data acquisition and synchronization: (1) Real-time acquisition of current signal of charging facility through high-precision fluxgate sensor (16-bit ADC, 10kS / s sampling rate); (2) Synchronous acquisition of voltage signal (24-bit Σ-Δ ADC, 10kS / s sampling rate) and temperature data (PT1000 sensor); (3) Second-level time synchronization (deviation <1μs) is achieved by using improved IEEE 1588 protocol (PTP); (4) Standard source data is received through HPLC module and timestamped with locally acquired data.

[0035] 2. Signal quality enhancement: (1) Hardware-level π-type filter network (L=2mH, C=0.1μF) filters out high-frequency switching noise; (2) Digital bandpass filter (1kHz-20kHz) eliminates noise interference above 30kHz generated by the charger; (3) OFDM modulation technology (128 subcarriers, 2MHz bandwidth) is used to improve the transmission quality of the power line channel; (4) Dynamic gain control (10×-1000× adjustable) ensures that the signal amplitude is within the optimal quantization range.

[0036] 3. Temperature compensation processing: (1) Real-time monitoring of ambient temperature based on PT1000 temperature sensor; (2) Correction of temperature drift effect of fluxgate sensor by 5th order polynomial compensation algorithm; (3) Compensation range covers -40℃~85℃, and temperature drift is controlled at <10ppm / ℃.

[0037] 4. Data integrity verification: (1) CRC-32 check ensures data transmission integrity; (2) Abnormal data triggers ARQ automatic retransmission mechanism (retransmission success rate >99.9%); (3) Data range rationality check (voltage 170-250V, current 0-250A, etc.).

[0038] In this embodiment, the formula for calculating the electricity metering error is: e e = (( E meas - E std ) / E std )×100% In the formula, e e This indicates the electrical energy metering error. E meas This indicates the electrical energy value measured by the tested charging facility. E std This indicates the electrical energy value measured by a standard electricity meter.

[0039] It should be noted here that dynamic error analysis involves: (1) real-time acquisition of the pulse signal output from the charging facility (1000 imp / kWh); (2) synchronous recording of the pulse output from the standard meter; and (3) counting the number of pulses within the same time window (usually 60 seconds). Therefore, E meas The calculation formula is: E meas = ( N meas ×3600) / (1000× t ) In the formula, Nmeas This indicates the pulse count of the meter under test. t Indicates the measurement time; E std The calculation formula is: E std = ( N std ×3600) / (1000× t ) In the formula, N std This indicates the standard meter pulse count.

[0040] The formula for calculating clock synchronization error is: e t = (( T local - T standard ) / T standard )×100% In the formula, e t This indicates the clock synchronization error. T local Indicates the local clock time of the tested charging facility. T standard The time of the standard time source is indicated. The improved IEEE 1588 protocol is used here to implement: (1) master-slave clock deviation measurement; (2) transmission delay compensation; (3) clock frequency adjustment.

[0041] The formula for calculating the overall error is: In the formula, e This represents the overall error. e h This indicates the harmonic influence error. α , β , c This represents the weighting coefficient (as defined in JJG 1148-2022).

[0042] 3. Determine whether the overall error exceeds the threshold. If it does, the measurement is deemed unqualified and a report is generated. Otherwise, the measurement is deemed qualified and a corresponding certificate is generated. It should be noted that the threshold can be set according to the national verification procedure JJG 1148-2022: (1) Working error: ≤ ±0.2% (0.5 grade); (2) Clock error: ≤ ±1s (full temperature range).

[0043] In this embodiment, the platform performs temperature drift compensation on the current waveform data using a lookup table method, covering a range from -40℃ to 85℃. When calculating the energy metering error, the platform simultaneously analyzes the harmonic distortion rate in the current waveform, triggering an early warning when the harmonic distortion rate exceeds a threshold. The adjustment coefficient is sent to the charging facility via a command frame with command word 0x02, and the command frame load includes a K coefficient for correcting the energy metering. This embodiment allows for real-time monitoring of the charging facility's operating status via an online verification module, monitoring every charging order around the clock and automatically issuing warnings for any abnormalities. Furthermore, the platform can dynamically allocate detection priorities based on the charging pile group status (e.g., communication quality, current magnitude), prioritizing high-current fast charging piles (>150A) to ensure the reliability of critical order metering. Additionally, a dedicated retransmission channel is allocated to harmonic distortion alarm piles, enabling second-level location of faulty piles.

[0044] In summary, compared with existing charging facility metering methods, the HPLC-based online high-precision metering method for charging facilities in this embodiment has the following advantages: 1. This HPLC-based online high-precision metrology method for charging facilities significantly improves efficiency (by more than 20 times) through online verification of charging facilities. Traditional manual verification of a single charging pile takes 2 hours (including on-site disassembly, assembly, and testing), while this metrology method can reduce the time to within a few minutes (up to within 6 minutes) through remote online verification. It can also support the concurrent verification of multiple charging piles (laboratory test data shows that it can simultaneously verify 3000 charging piles). Through the deep integration of HPLC communication and metrology technology, it systematically solves the problems of real-time performance, economy, and accuracy in charging facility verification, breaks through the limitations of traditional periodic verification, and achieves continuous metrological performance tracking once per minute. It can promptly detect gradual faults such as CT saturation and ADC drift (e.g., a charging pile triggering three consecutive harmonic out-of-tolerance alarms). This solves the technical problems of low verification efficiency and poor accuracy in existing charging facility metrology methods.

[0045] 2. This HPLC-based online high-precision metering method for charging facilities enables integrated power line-communication transmission. This method reuses the charging pile's power supply line for data communication, eliminating the need for additional wiring and reducing deployment costs. It also supports high-frequency data transmission (10kS / s sampling rate), meeting the requirements of JJG 1148-2022 for dynamic energy metering. Furthermore, employing multi-band adaptive modulation technology (such as a 2-12MHz adjustable carrier), it maintains communication stability (bit error rate <10%) even under high-frequency switching noise (above 30kHz) from the charger. 6 ).

[0046] 3. This HPLC-based online high-precision metering method for charging facilities can achieve low-latency time synchronization. Based on an improved IEEE 1588 (PTP) protocol, this method achieves sub-microsecond synchronization (deviation <1μs) between the verification end and the standard clock source via the HPLC channel, ensuring the timing consistency of the metering data. Furthermore, it dynamically compensates for power line transmission delay, resolving the clock drift problem caused by network jitter in traditional RS-485 / 4G solutions.

[0047] 4. This HPLC-based online high-precision metrology method for charging facilities ensures secure encryption and data integrity. The method employs an encryption algorithm to perform end-to-end encryption of verification commands and metrological data, preventing man-in-the-middle attacks. Furthermore, each data packet is appended with a CRC-32 checksum, and abnormal data automatically triggers a retransmission mechanism (retransmission success rate >99.9%).

[0048] 5. The HPLC-based online high-precision metering method for charging facilities innovatively applies a fluxgate sensor to the current measurement of charging piles, which can achieve: (1) wide dynamic range and high-precision detection. Using closed-loop fluxgate technology, a current measurement accuracy of ±0.05% is achieved in the range of 5A-250A (better than the ±0.2% of the traditional Hall sensor), which is especially suitable for high-current fast charging scenarios (such as 800V high-voltage platforms). Furthermore, the measurement drift problem of charging piles in outdoor environments can be solved by using a temperature compensation algorithm (temperature drift <10ppm / ℃ from -40℃ to 85℃). (2) Harmonic anti-interference capability. The fluxgate sensor is based on the principle of magnetic field induction and has natural anti-interference capability against high-frequency harmonics (such as noise above 50kHz generated by the charger). Compared with traditional shunts, it can reduce the harmonic influence by more than 90%. Combined with real-time FFT analysis, harmonic components are dynamically eliminated to ensure that the fundamental energy metering error is ≤0.1%. (3) Non-contact measurement. Non-invasive installation (no need to disconnect the main circuit), supports online replacement and calibration, avoiding the risk of metering failure caused by magnetic saturation of traditional CTs (current transformers).

[0049] Example 2 This embodiment provides an online high-precision metering device for charging facilities based on HPLC, which applies the online high-precision metering method for charging facilities based on HPLC from Embodiment 1. The metering device includes a data acquisition system, an error detection system, and an out-of-limit determination system.

[0050] The data acquisition system sends acquisition commands to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, and drives the fluxgate sensor to acquire current signals in real time. All signals are transmitted back to the platform via the HPLC module. The error detection system first preprocesses the received signals to obtain real-time data, then compares the real-time data with standard source data to calculate three errors: energy metering error, clock synchronization error, and harmonic interference error. Finally, it calculates the comprehensive error based on these three errors. The over-limit judgment system determines whether the comprehensive error exceeds a threshold. If it does, the measurement is deemed unqualified and a report is generated; otherwise, the measurement is deemed qualified and a corresponding certificate is generated.

[0051] Example 3 This embodiment provides a computer terminal, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the HPLC-based online high-precision metering method for charging facilities described in Embodiment 1.

[0052] The method in Example 1 can be applied in software form, such as by designing it as a standalone program and installing it on a computer terminal, which can be a computer, smartphone, control system, or other IoT device. Alternatively, the method in Example 1 can be designed as an embedded program and installed on a computer terminal, such as on a microcontroller.

[0053] Example 4 This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it implements the steps of the HPLC-based online high-precision metering method for charging facilities described in Embodiment 1.

[0054] When applying the method of Example 1, it can be applied in the form of software, such as by designing it as a program that can run independently on a computer-readable storage medium. The computer-readable storage medium can be a USB flash drive, designed as a USB security token, and the program can be designed to start the entire method through an external trigger.

[0055] Example 5 This embodiment provides an application scheme of the charging facility metering method based on Embodiment 1 in a supercharging station.

[0056] 1. Hardware deployment: (1) Install a wideband fluxgate sensor (range extended to ±500A, bandwidth DC-100kHz) in the main circuit of the 480kW liquid-cooled supercharging pile (output voltage 800V). (2) Upgrade the HPLC module to dual-band communication (CENELEC-A band + 2-30MHz industrial band), and use MIMO technology to improve channel capacity.

[0057] 2. Dynamic accuracy assurance: (1) For the 300A / μs current step of the supercharging pile, the pre-saturation drive mode is enabled: 10ms before the current ramp-up period, the H-bridge excitation voltage is increased to ±12V to avoid transient saturation of the magnetic core. (2) The platform performs online calibration once every 100ms in the constant current stage according to the IEC61851-23 standard (60 times faster than conventional piles).

[0058] The above solution can significantly reduce the annual inspection cost per station, and the compensation for measurement disputes is significantly reduced.

[0059] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A high-precision online metering method for charging facilities based on HPLC, characterized in that, The charging facility is equipped with an HPLC module and a fluxgate sensor; the measurement method includes the following steps: The system sends acquisition commands to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, and drives the fluxgate sensor to acquire current signals in real time. All signals are transmitted back to the platform through the HPLC module. First, the platform preprocesses the received signal to obtain real-time data. Then, the real-time data is compared with standard source data to calculate three errors: power metering error, clock synchronization error, and harmonic influence error. Finally, the comprehensive error is calculated based on the three errors. Determine whether the comprehensive error exceeds the threshold. If it does, the measurement is deemed unqualified and a report is generated. Otherwise, the measurement is deemed qualified and a corresponding certificate is generated. The formula for calculating the electricity metering error is as follows: ε e = (( E meas - E std ) / E std )×100% In the formula, ε e This indicates the electrical energy metering error. E meas This indicates the electrical energy value measured by the tested charging facility. E std This indicates the electrical energy value measured by a standard electricity meter. The formula for calculating clock synchronization error is: ε t = (( T local - T standard ) / T standard )×100% In the formula, ε t This indicates the clock synchronization error. T local Indicates the local clock time of the tested charging facility. T standard Indicates the time of the standard time source; The formula for calculating the overall error is: In the formula, ε This represents the overall error. ε h This indicates the harmonic influence error. α , β , γ Indicates the weighting coefficient; E meas The calculation formula is: E meas = ( N meas ×3600) / (1000× t ) In the formula, N meas This indicates the pulse count of the meter under test. t Indicates the measurement time; E std The calculation formula is: E std = ( N std ×3600) / (1000× t ) In the formula, N std Indicates the standard meter pulse count; The HPLC module uses a π-type filter network for high-frequency noise isolation, and the filter network parameters are: inductance L=2mH, capacitance C=0.1μF; the fluxgate sensor uses a nanocrystalline alloy core, and the linear measurement range covers ±250A, and is equipped with an H-bridge drive circuit with 10kHz square wave excitation. The acquisition command is issued using a TDMA (Time Division Multiple Access) mechanism with a time slot width of 10ms. The data packet structure includes a frame header of 0xAA55, a data length field, a command word field, payload data, a CRC16 check field, and a frame tail of 0x55AA. All signal return data carries a timestamp synchronized by the IEEE 1588 protocol, and the time synchronization deviation between the platform and the charging facility is less than 1μs. The output signal of the fluxgate sensor passes through a bandpass filter and a two-stage amplification circuit in sequence, and is converted into a digital signal by a 24-bit Σ-Δ ADC; the fluxgate sensor has a built-in PT1000 temperature sensor, and the temperature signal is acquired through the PT1000 temperature sensor.

2. The online high-precision metering method for charging facilities based on HPLC as described in claim 1, characterized in that, The platform performs temperature drift compensation on the current waveform data using a lookup table method, with the compensation range covering -40℃ to 85℃. When calculating the power metering error, the platform simultaneously analyzes the harmonic distortion rate in the current waveform, and triggers an early warning when the harmonic distortion rate exceeds a threshold.

3. A high-precision online metering device for charging facilities based on HPLC, characterized in that, Its application is the online high-precision metering method for charging facilities based on HPLC as described in claim 1 or 2; the device includes: The data acquisition system is used to send acquisition commands to the HPLC module via the power line to trigger the charging facility to acquire voltage, temperature, pulse, and clock signals, drive the fluxgate sensor to acquire current signals in real time, and transmit all signals back to the platform through the HPLC module. The error detection system is used to first enable the platform to preprocess the received signal to obtain real-time data, then compare the real-time data with standard source data, calculate three errors: power metering error, clock synchronization error, and harmonic influence error, and finally calculate the comprehensive error based on the three errors. The over-limit determination system is used to determine whether the comprehensive error exceeds the threshold. If it does, the measurement is deemed unqualified and a report is generated; otherwise, the measurement is deemed qualified and a corresponding certificate is generated.

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